In general, humans cannot easily cope with multivariate problems (i.e., decisions that have multiple potential solutions). One current approach to facilitate decision-making is to hold workshops where different solutions can be discussed and explained in a group/collaborative environment. In most cases, a considerable amount of information (e.g., data and opinions) is gathered in advance of and/or during the workshop. Navigating through this information and presenting it in a format that can be easily parsed and understood by workshop attendees continues to be a problem. Currently, this problem is addressed through the use of static charts and presentations that have been previously prepared from the source data. Occasionally, dynamic simple bar charts or graphs are used to supplement static charts. In the field of mathematics, there are specialized computational techniques for addressing data integration and display issues, but these methods typically require significant expertise to execute and are not easily customized.
Unfortunately, the current approaches have several drawbacks such as: (1) a lack of responsiveness to opinion data gathered during the work session itself; (2) no dynamic change capability to consider alternatives; (3) bar charts or graphs generally are limited to two or three dimensions and do not support the need to consider a larger number of variables simultaneously; (4) complex mathematical models exist to do, for example, optimization, but they don't easily incorporate opinion and other forms of qualitative data necessary for consensus-building and executive decision-making.
In view of the foregoing, a need exists for a solution that solves at least one of the deficiencies of the related at.